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Current Trends in Research on Bone Regeneration: A Bibliometric Analysis
BACKGROUND: Bone regeneration is a frequent research topic in clinical studies, but macroscopic studies on the clinical application of bone regeneration are rare. We conducted a bibliometric analysis, using international databases, to explore the clinical application and mechanism of bone regenerati...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273498/ https://www.ncbi.nlm.nih.gov/pubmed/32685539 http://dx.doi.org/10.1155/2020/8787394 |
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author | Huang, Xin Liu, Xu Shang, Yuli Qiao, Feng Chen, Gang |
author_facet | Huang, Xin Liu, Xu Shang, Yuli Qiao, Feng Chen, Gang |
author_sort | Huang, Xin |
collection | PubMed |
description | BACKGROUND: Bone regeneration is a frequent research topic in clinical studies, but macroscopic studies on the clinical application of bone regeneration are rare. We conducted a bibliometric analysis, using international databases, to explore the clinical application and mechanism of bone regeneration, to highlight the relevant research hotspots and prospects. Material and Methods. Scientific reports on bone regeneration published during 2009–2019 were retrieved from PubMed. VOSviewer for cooccurrence keywords and authorship analysis. BICOMB software was used to retrieve high-frequency words and construct a text/coword matrix. The matrix was inputted into gCLUTO software, managed by biclustering analysis, in order to identify hotspots, which could achieve mountain and matrix visualizations. The matrix was also analyzed by using Ucinet 6 software for social network analysis. A strategic diagram was used for further analysis of the research hotspots of bone regeneration by “SCIMAT” software. We searched the Web of Science for relevant articles. RESULTS: Eighty-nine high-frequency major MeSH terms were obtained from 10237 articles and were divided into 5 clusters. We generated a network visualization map, an overlay visualization mountain map, and a social network diagram. Then, the MeSH terms were subdivided into 7 categories according to each diagram; current research hotspots were identified as scaffold, drug effect, osseointegration in dental implant, guided bone regeneration, factors impacting bone regeneration, treatment of bone and tissue loss, and bone regeneration in dental implants. CONCLUSION: BICOMB, VOSviewer, and other bibliometric tools revealed that dental implants, scaffolds, and factors impacting bone regeneration are hot research topics, while scaffolds also hold promise from the perspective of bone tissue regeneration. |
format | Online Article Text |
id | pubmed-7273498 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-72734982020-07-17 Current Trends in Research on Bone Regeneration: A Bibliometric Analysis Huang, Xin Liu, Xu Shang, Yuli Qiao, Feng Chen, Gang Biomed Res Int Research Article BACKGROUND: Bone regeneration is a frequent research topic in clinical studies, but macroscopic studies on the clinical application of bone regeneration are rare. We conducted a bibliometric analysis, using international databases, to explore the clinical application and mechanism of bone regeneration, to highlight the relevant research hotspots and prospects. Material and Methods. Scientific reports on bone regeneration published during 2009–2019 were retrieved from PubMed. VOSviewer for cooccurrence keywords and authorship analysis. BICOMB software was used to retrieve high-frequency words and construct a text/coword matrix. The matrix was inputted into gCLUTO software, managed by biclustering analysis, in order to identify hotspots, which could achieve mountain and matrix visualizations. The matrix was also analyzed by using Ucinet 6 software for social network analysis. A strategic diagram was used for further analysis of the research hotspots of bone regeneration by “SCIMAT” software. We searched the Web of Science for relevant articles. RESULTS: Eighty-nine high-frequency major MeSH terms were obtained from 10237 articles and were divided into 5 clusters. We generated a network visualization map, an overlay visualization mountain map, and a social network diagram. Then, the MeSH terms were subdivided into 7 categories according to each diagram; current research hotspots were identified as scaffold, drug effect, osseointegration in dental implant, guided bone regeneration, factors impacting bone regeneration, treatment of bone and tissue loss, and bone regeneration in dental implants. CONCLUSION: BICOMB, VOSviewer, and other bibliometric tools revealed that dental implants, scaffolds, and factors impacting bone regeneration are hot research topics, while scaffolds also hold promise from the perspective of bone tissue regeneration. Hindawi 2020-05-27 /pmc/articles/PMC7273498/ /pubmed/32685539 http://dx.doi.org/10.1155/2020/8787394 Text en Copyright © 2020 Xin Huang et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Huang, Xin Liu, Xu Shang, Yuli Qiao, Feng Chen, Gang Current Trends in Research on Bone Regeneration: A Bibliometric Analysis |
title | Current Trends in Research on Bone Regeneration: A Bibliometric Analysis |
title_full | Current Trends in Research on Bone Regeneration: A Bibliometric Analysis |
title_fullStr | Current Trends in Research on Bone Regeneration: A Bibliometric Analysis |
title_full_unstemmed | Current Trends in Research on Bone Regeneration: A Bibliometric Analysis |
title_short | Current Trends in Research on Bone Regeneration: A Bibliometric Analysis |
title_sort | current trends in research on bone regeneration: a bibliometric analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273498/ https://www.ncbi.nlm.nih.gov/pubmed/32685539 http://dx.doi.org/10.1155/2020/8787394 |
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